A Framework for Integration of Artificial Intelligence Into Digital Marketing in Jordanian Commercial Banks.

This paper investigates the relationship between artificial intelligence (AI), and digital marketing in the Jordanian banking sector. It outlines the main implications of information gathering, data modelling, and processing & delivery, as well, the importance of human communication and ethical implications. Banks need a coherent foundation when employing AI. This paper provides a theoretical background for AI developers, policymakers and marketers in the banking sector, and academics. Despite the extensive employment of artificial intelligence in numerous global and local businesses, few studies addressed the use of AI in the Jordanian banking sector. As well, AI has rapidly changed digital marketing practices, particularly in the light of the Coronavirus (COVID_19) pandemic. Banks in Jordan are oblivious to the challenges they face when integrating AI into their digital marketing services. This paper derives a general framework for integrating AI techniques into digital marketing practices in Jordanian banks. Recommendations designed to assist banks in targeting their clients more efficiently also presented in this paper. &nbsp

Innovative Marketing Approach in Project Management: a Market Orientation Perspective

The main objective of this paper is to develop an integrated conceptual framework to achieve consistency and synergy between project management and e-marketing activities within the market orientation that depends on the transaction, database, interactive and network marketing. The study solicited to apply this model in development or commercial projects conducted in Jordan. To extend this, the researcher interviewed people with experience who work in various projects such as educational projects or developing information technology systems, infrastructure projects, development projects, and others. The researcher was able to interview 34 experienced managers, and the interview form included a set of open questions related to the four dimensions of marketing orientation. The interview questions included covering how to integrate e-marketing activities into project management, it has directed in such a way as to highlight which marketing trends are most appropriate for the type of project and the duration of its implementation. The researcher identified most appropriate marketing trends for each project type and suggested which electronic marketing tools are most suitable for project managers and employees to adapt to communicate with individual clients or organizations, or even with other parties who have a direct or indirect relationship with the project such as stakeholders, suppliers and others.  The implication for practitioners in the projects suggested, and recommendations for future research to generalize the proposed conceptual framework also presented. &nbsp

Modeling and Optimization of a Compression Ignition Engine Fueled with Biodiesel Blends for Performance Improvement

Biodiesel is considered to be a promising alternative option to diesel fuel. The main contribution of the current work is to improve compression ignition engine performance, fueled by several biodiesel blends. Three metrics were used to evaluate the output performance of the compression ignition engine, as follows: brake torque (BT), brake specific fuel consumption (BSFC), and brake thermal efficiency (BTE), by varying two input parameters (engine speed and fuel type). The engine speeds were in the 1200–2400 rpm range. Three biodiesel blends, containing 20 vol.% of vegetable oil and 80 vol.% of pure diesel fuel, were prepared and tested. In all the experiments, pure diesel fuel was employed as a reference for all biodiesel blends. The experimental results revealed the following findings: although all types of biodiesel blends have low calorific value and slightly high viscosity, as compared to pure diesel fuel, there was an improvement in both BT and brake power (BP) outputs. An increase in BSFC by 7.4%, 4.9%, and 2.5% was obtained for palm, sunflower, and corn biodiesel blends, respectively, as compared to that of pure diesel. The BTE of the palm oil biodiesel blend was the lowest among other biodiesel blends. The suggested work strategy includes two stages (modeling and parameter optimization). In the first stage, a robust fuzzy model is created, depending on the experimental results, to simulate the output performance of the compression ignition engine. The particle swarm optimization (PSO) algorithm is used in the second stage to determine the optimal operating parameters. To confirm the distinction of the proposed strategy, the obtained outcomes were compared to those attained by response surface methodology (RSM). The coefficient of determination (R2) and the root-mean-square-error (RMSE) were used as comparison metrics. The average R2 was increased by 27.7% and 29.3% for training and testing, respectively, based on the fuzzy model. Using the proposed strategy in this work (integration between fuzzy logic and PSO) may increase the overall performance of the compression ignition engine by 2.065% and 8.256%, as concluded from the experimental tests and RSM

Modeling and Optimization of a Compression Ignition Engine Fueled with Biodiesel Blends for Performance Improvement

Biodiesel is considered to be a promising alternative option to diesel fuel. The main contribution of the current work is to improve compression ignition engine performance, fueled by several biodiesel blends. Three metrics were used to evaluate the output performance of the compression ignition engine, as follows: brake torque (BT), brake specific fuel consumption (BSFC), and brake thermal efficiency (BTE), by varying two input parameters (engine speed and fuel type). The engine speeds were in the 1200–2400 rpm range. Three biodiesel blends, containing 20 vol.% of vegetable oil and 80 vol.% of pure diesel fuel, were prepared and tested. In all the experiments, pure diesel fuel was employed as a reference for all biodiesel blends. The experimental results revealed the following findings: although all types of biodiesel blends have low calorific value and slightly high viscosity, as compared to pure diesel fuel, there was an improvement in both BT and brake power (BP) outputs. An increase in BSFC by 7.4%, 4.9%, and 2.5% was obtained for palm, sunflower, and corn biodiesel blends, respectively, as compared to that of pure diesel. The BTE of the palm oil biodiesel blend was the lowest among other biodiesel blends. The suggested work strategy includes two stages (modeling and parameter optimization). In the first stage, a robust fuzzy model is created, depending on the experimental results, to simulate the output performance of the compression ignition engine. The particle swarm optimization (PSO) algorithm is used in the second stage to determine the optimal operating parameters. To confirm the distinction of the proposed strategy, the obtained outcomes were compared to those attained by response surface methodology (RSM). The coefficient of determination (R2) and the root-mean-square-error (RMSE) were used as comparison metrics. The average R2 was increased by 27.7% and 29.3% for training and testing, respectively, based on the fuzzy model. Using the proposed strategy in this work (integration between fuzzy logic and PSO) may increase the overall performance of the compression ignition engine by 2.065% and 8.256%, as concluded from the experimental tests and RSM